Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

CudnnRNNParamsToCanonicalV2

public final class CudnnRNNParamsToCanonicalV2

Retrieves CudnnRNN params in canonical form. It supports the projection in LSTM.

Retrieves a set of weights from the opaque params buffer that can be saved and restored in a way compatible with future runs.

Note that the params buffer may not be compatible across different GPUs. So any save and restoration should be converted to and from the canonical weights and biases.

num_layers: Specifies the number of layers in the RNN model. num_units: Specifies the size of the hidden state. input_size: Specifies the size of the input state. num_params_weights: number of weight parameter matrix for all layers. num_params_biases: number of bias parameter vector for all layers. weights: the canonical form of weights that can be used for saving and restoration. They are more likely to be compatible across different generations. biases: the canonical form of biases that can be used for saving and restoration. They are more likely to be compatible across different generations. rnn_mode: Indicates the type of the RNN model. input_mode: Indicate whether there is a linear projection between the input and The actual computation before the first layer. 'skip_input' is only allowed when input_size == num_units; 'auto_select' implies 'skip_input' when input_size == num_units; otherwise, it implies 'linear_input'. direction: Indicates whether a bidirectional model will be used. dir = (direction == bidirectional) ? 2 : 1 dropout: dropout probability. When set to 0., dropout is disabled. seed: the 1st part of a seed to initialize dropout. seed2: the 2nd part of a seed to initialize dropout. num_proj: The output dimensionality for the projection matrices. If None or 0, no projection is performed.

Nested Classes

class CudnnRNNParamsToCanonicalV2.Options Optional attributes for CudnnRNNParamsToCanonicalV2

Public Methods

List< Output <T>>
static <T extends Number> CudnnRNNParamsToCanonicalV2 <T>
create ( Scope scope, Operand <Integer> numLayers, Operand <Integer> numUnits, Operand <Integer> inputSize, Operand <T> params, Long numParamsWeights, Long numParamsBiases, Options... options)
Factory method to create a class wrapping a new CudnnRNNParamsToCanonicalV2 operation.
static CudnnRNNParamsToCanonicalV2.Options
direction (String direction)
static CudnnRNNParamsToCanonicalV2.Options
dropout (Float dropout)
static CudnnRNNParamsToCanonicalV2.Options
inputMode (String inputMode)
static CudnnRNNParamsToCanonicalV2.Options
numProj (Long numProj)
static CudnnRNNParamsToCanonicalV2.Options
rnnMode (String rnnMode)
static CudnnRNNParamsToCanonicalV2.Options
seed (Long seed)
static CudnnRNNParamsToCanonicalV2.Options
seed2 (Long seed2)
List< Output <T>>

Inherited Methods

Public Methods

public List< Output <T>> biases ()

public static CudnnRNNParamsToCanonicalV2 <T> create ( Scope scope, Operand <Integer> numLayers, Operand <Integer> numUnits, Operand <Integer> inputSize, Operand <T> params, Long numParamsWeights, Long numParamsBiases, Options... options)

Factory method to create a class wrapping a new CudnnRNNParamsToCanonicalV2 operation.

Parameters
scope current scope
options carries optional attributes values
Returns
  • a new instance of CudnnRNNParamsToCanonicalV2

public static CudnnRNNParamsToCanonicalV2.Options direction (String direction)

public static CudnnRNNParamsToCanonicalV2.Options dropout (Float dropout)

public static CudnnRNNParamsToCanonicalV2.Options inputMode (String inputMode)

public static CudnnRNNParamsToCanonicalV2.Options numProj (Long numProj)

public static CudnnRNNParamsToCanonicalV2.Options rnnMode (String rnnMode)

public static CudnnRNNParamsToCanonicalV2.Options seed (Long seed)

public static CudnnRNNParamsToCanonicalV2.Options seed2 (Long seed2)

public List< Output <T>> weights ()